该研究的目的是确定与标准 3D LapPass 训练模型相比，使用维度和空间复杂性更高的 3D 增强训练模型来获取腹腔镜技能是否会更好。我们假设，在 2D 视觉模态中采用低保真、3D 增强训练模型可能会加快对与深度知觉相关的单眼线索的适应，从而提高表现。一项前瞻性、单中心、2 臂、随机对照试验，参与者随机随机化分为 3D 增强组或标准 3D 组（分配比 1:1，块尺寸 2 和 4），执行 2 项标准化腹腔镜任务：(1) polo 抓取和操作以及 (2) 体内缝合。使用腹腔镜技能全球手术评估 (GOALS) 工具、完成时间和错误数量来评估绩效，并对每项任务的基线、中期和培训后进行评估。一项研究后调查测量了参与者的自信心和表现（ID：NCT06184854）。英国伦敦玛丽女王大学巴茨癌症研究所。招收了 65 名医学生，全部是腹腔镜手术新手，其中 3 名中途退出。30 名- 每组中有一名参与者完成了研究，人口统计数据具有同质性 (p > 0.05)。与 2 项任务的基线相比，两组在训练后的表现均显着优于基线（组内比较，p < 0.017）。在组间比较中，在两项任务的所有比较中，3D 增强组在目标评分参数和深度感知域方面都有统计学上显着的改善（p < 0.05）。然而，时间改进和错误减少也有利于 3D 增强组，但未达到统计显着性。在研究后调查中，3D 增强组报告称，在单独的缝合任务中，训练后的信心和表现明显更高 (p < 0.05)。使用 3D 增强训练模型可以让新手获得更好的腹腔镜技能。与标准 3D LapPass 模型相比，任务数减少了 2 个。因此，将 3D 增强模型与标准 3D LapPass 模型一起纳入腹腔镜培训课程可以补充学习。进一步的工作应侧重于基于能力的终点的长期功效。版权所有 © 2024 作者。由爱思唯尔公司出版。保留所有权利。

The aim of the study was to determine if laparoscopic skills acquisition will be superior with the use of 3D-enhanced training models with increased dimensionality and spatial complexity compared to standard 3D LapPass training models in novice medical students. We hypothesized that adopting low-fidelity, 3D-enhanced training models in the 2D visual modality may expedite adaptation to monocular cues related to depth perception, enhancing performance.A prospective, single-center, 2-arm, randomized controlled trial with participants randomized equally into either 3D-enhanced or standard 3D group (allocation ratio 1:1, block sizes 2 and 4) performing 2 standardized laparoscopic tasks: (1) polo grasping and manipulation and (2) intracorporeal suturing. Performance was assessed using the Global Operative Assessment of Laparoscopic Skills (GOALS) tool, completion time, and number of errors, with evaluations at baseline, interim, and post-training for each task. A post-study survey measured participant-perceived confidence and performance (ID: NCT06184854).Barts Cancer Institute, Queen Mary University of London, UK.Sixty-five medical students, all novices in laparoscopic surgery, were enrolled, with 3 dropouts.Thirty-one participants in each group completed the study with homogeneity regarding demographic data (p > 0.05). Both groups had significantly superior performance post-training compared to baseline in the 2 tasks (intragroup comparison, p < 0.017). In the intergroup comparison, the 3D-enhanced group had statistically significantly greater improvements in the GOALS score parameter and depth perception domain across all comparisons for both tasks (p < 0.05). Time improvement and error reduction also favored the 3D-enhanced group, however, without reaching statistical significance. In the post-study survey, the 3D-enhanced group reported significantly greater perceived post-training confidence and performance in the suturing task alone (p < 0.05).The use of 3D-enhanced training models resulted in superior laparoscopic skills acquisition for novices in 2 tasks compared to standard 3D LapPass models. Therefore, incorporating 3D-enhanced models into laparoscopic training curricula alongside standard 3D LapPass models can supplement learning. Further work should focus on long-term efficacy with a competency-based endpoint.Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.